US10460269B1ActiveUtility

Space dataset optimization

Assignee: MASTERCARD INTERNATIONAL INCPriority: Jul 18, 2017Filed: Jul 18, 2017Granted: Oct 29, 2019
Est. expiryJul 18, 2037(~11 yrs left)· nominal 20-yr term from priority
G06Q 30/0201G06Q 10/06315
69
PatentIndex Score
1
Cited by
36
References
20
Claims

Abstract

Disclosed method comprises receiving from a user interface, a request to generate an optimized space dataset; generating a first instruction configured to receive a first dataset comprising at least one of a space allocated to the product, product attribute, and product performance value corresponding to a plurality of institutions; automatically calculating an elasticity range based on the space allocated to the product; calculating an unbounded asymptote and elasticity values; upon the unbounded elasticity value being outside the elasticity range, dynamically adjusting the elasticity value based on the elasticity range; iteratively calculating a bounded asymptote value based on the second dataset data points until the asymptote value is within the adjusted elasticity range; and generating a graphical representation to illustrate an optimized space trend comprising plurality of data points.

Claims

exact text as granted — not AI-modified
What is claimed is: 
     
       1. A method comprising:
 receiving, by a server from a user interface, a request to generate an optimized space dataset, wherein the received request comprises identification associated with a product and a first institution; 
 generating, by the server, a first instruction configured to receive a first dataset comprising at least one of a space allocated to the product, product attribute, and product performance value corresponding to a plurality of institutions, wherein the plurality of institutions comprises at least the first institution; 
 upon transmitting the first instruction to a first database, receiving, by the server, the first dataset; 
 identifying, by the server, a plurality of first dataset data points, wherein each first dataset data point corresponds to the space allocated to the product and the product performance value associated with the plurality of institutions; 
 automatically calculating, by the server, an elasticity range based on the space allocated to the product, wherein the elasticity range represents a maximum elasticity range value and a minimum elasticity range value each representing maximum and minimum product space value associated with the plurality of institutions; 
 determining, by the server, an unbounded elasticity value and a corresponding asymptote value based on a second dataset, wherein the second dataset comprises second dataset data points corresponding to space allocated to the product and the product performance value associated with the first institution; 
 in response to the unbounded elasticity value being outside the elasticity range, dynamically adjusting, by the server, the elasticity value based on the elasticity range; 
 iteratively calculating, by the server, a bounded asymptote value and a bounded elasticity value based on the second dataset data points until the bounded asymptote and elasticity values are within the adjusted elasticity range, wherein a number of iterative calculations is based on the adjusted elasticity range and an incremental value; 
 generating, by the server, a graphical representation of the second dataset data points, wherein the graphical representation is configured to illustrate an optimized space trend comprising plurality of data points; and 
 generating, by the server, a second instruction configured to display plurality of second set data points on the user interface. 
 
     
     
       2. The method of  claim 1 , wherein the minimum elasticity value is calculated by multiplying a second percentile of space allocated to the product within a plurality of spaces allocated to the product within the plurality of institutions by a first multipliers. 
     
     
       3. The method of  claim 2 , wherein the first multiplier is about 0.922. 
     
     
       4. The method of  claim 2 , wherein the first multiplier is received, by the server, from the user interface. 
     
     
       5. The method of  claim 1 , wherein the minimum elasticity value is calculated by multiplying 98th percentile of space allocated to the product within a plurality of spaces allocated to the product within the plurality of institutions by a second multipliers. 
     
     
       6. The method of  claim 5 , wherein the second multiplier is about 3. 
     
     
       7. The method of  claim 5 , wherein the second multiplier is about 3.5. 
     
     
       8. The method of  claim 5 , wherein the second multiplier is received, by the server, from the user interface. 
     
     
       9. The method of  claim 1 , wherein the incremental value is received, by the server, from the user interface. 
     
     
       10. The method of  claim 1 , wherein the first dataset is received, by the server, from the user interface. 
     
     
       11. A computer system comprising:
 a server configured to:
 receive from a user interface, a request to generate an optimized space dataset, wherein the received request comprises identification associated with a product and a first institution; 
 generate a first instruction configured to receive a first dataset comprising at least one of a space allocated to the product, product attribute, and product performance value corresponding to a plurality of institutions, wherein the plurality of institutions comprises at least the first institution; 
 upon transmitting the first instruction to a first database, receive the first dataset; 
 identify a plurality of first dataset data points, wherein each first dataset data point corresponds to the space allocated to the product and the product performance value associated with the plurality of institutions; 
 automatically calculate an elasticity range based on the space allocated to the product, wherein the elasticity range represents a maximum elasticity range value and a minimum elasticity range value each representing maximum and minimum product space value associated with the plurality of institutions; 
 determine an unbounded elasticity value and a corresponding asymptote value based on a second dataset, wherein the second dataset comprises second dataset data points corresponding to space allocated to the product and the product performance value associated with the first institution; 
 in response to the unbounded elasticity value being outside the elasticity range, dynamically adjusting, by the server, the elasticity value based on the elasticity range; 
 iteratively calculate a bounded asymptote value and a bounded elasticity value based on the second dataset data points until the bounded asymptote and elasticity values are within the adjusted elasticity range, wherein a number of iterative calculations is based on the adjusted elasticity range and an incremental value; 
 generate a graphical representation of the second dataset data points, wherein the graphical representation is configured to illustrate an optimized space trend comprising plurality of data points; and 
 generate a second instruction configured to display plurality of second set data points on the user interface. 
 
 
     
     
       12. The computer system of  claim 11 , wherein the minimum elasticity value is calculated by multiplying 2 nd  percentile of space allocated to the product within the plurality of spaces by a first multipliers. 
     
     
       13. The computer system of  claim 12 , wherein the first multiplier is about 0.922. 
     
     
       14. The computer system of  claim 12 , wherein the first multiplier is received, by the server, from the user interface. 
     
     
       15. The computer system of  claim 11 , wherein the minimum elasticity value is calculated by multiplying 98th percentile of space allocated to the product within the plurality of spaces by a second multipliers. 
     
     
       16. The computer system of  claim 15 , wherein the second multiplier is about 3. 
     
     
       17. The computer system of  claim 15 , wherein the second multiplier is about 3.5. 
     
     
       18. The computer system of  claim 15 , wherein the second multiplier is received, by the server, from the user interface. 
     
     
       19. The computer system of  claim 11 , wherein the incremental value is received, by the server, from the user interface. 
     
     
       20. The computer system of  claim 11 , wherein the first dataset is received, by the server, from the user interface.

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